Download Projected GS signal

Is the lady dead, was she killed and by whom?
Changing rainfall in the past decades in Europe
Hans von Storch (HZG),
Armineh Barkhordarian (UCLA)
18. Juni 2015 - Abschlussveranstaltung des bilateralen Forschungsprojektes
"WETRAX - Veränderung des Risikos von großräumigen Starkniederschlägen
im Klimawandel in Mitteleuropa, mit Fokus auf atmosphärische Wetterlagen
und Zugbahnen", Wien
The issue is
deconstructing a given record
with the intention to identify „predictable“ components.
„Predictable“
-- either natural processes, which are known of having limited life times,
-- or man-made processes, which are subject to decisions (e.g., GHG, urban effect)
Differently understood in different social and scientific quarters.
The issue is also to help to discriminate between culturally
supported claims and scientifically warranted claims
The issue of deconstructing regional climate
change
We have examined to regions
- the Baltic Sea region, and
- the Med Sea Region
in the past decades of years, in light of the hypothesis that the changes are
related to atmospheric elevated greenhouse gas concentrations.
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Michael Schrenk, © vonStorch, HZG
BACC-II report, 2015
Michael Schrenk, © vonStorch, HZG
Michael Schrenk, © vonStorch, HZG
Observed temperature trends
in the Baltic Sea region (1982-2011)
Baltic Sea region
Observed CRU, EOBS (1982-2011)
95th-%tile of „non-GS“ variability,
derived from 2,000-year palaeo-simulations
Estimating natural variability:
2,000-year high-resolution regional climate
palaeo-simulation (Gómez-Navarro et al,
2013) is used to estimate natural (internal +
external) variability.
 An external cause is needed for explaining the recently observed annual and seasonal
warming over the Baltic Sea area, except for winter (with < 2.5% risk of error)
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2m Temperature in the Med Sea Region
(1980-2009)
Observed changes of 2m temperature
(1980-2009) in comparison with GS signals
Observed trends of 2m temperature (1980-2009)
Projected GS signal patterns, A1B scenario
23 AOGCMs, 49 simulations (CMIP3)
90% uncertainty range of observed trends, derived
from 10,000-year control simulations
The spread of trends of 23 climate change projections
DJF
MAM
JJA
SON
Annual
 There is less than 5% probability that natural (internal) variability is responsible for the observed
annual and seasonal warming in the Med Sea region, except in winter.
(Barkhordarian et al , Climate Dynamics 2012a)
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Michael Schrenk, © vonStorch, HZG
Michael Schrenk, © vonStorch, HZG
Observed and projected temperature
trends in the Baltic Sea Region (1982-2011)
Observed changes of 2m temperature
(1980-2009) in comparison with GS signals
Observed trends of 2m temperature (1980-2009)
Projected GS signal patterns, A1B scenario
23 AOGCMs, 49 simulations (CMIP3)
90% uncertainty range of observed trends, derived
from 10,000-year control simulations
The spread of trends of 23 climate change projections
DJF
MAM
JJA
SON
Annual
 In the Med Sea region, the warming can be explained by the A1B scenario of increased GHGs.
(Barkhordarian et al , Climate Dynamics 2012a)
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Observed and projected temperature
trends in the Baltic Sea Region (1982-2011)
Observed CRU, EOBS (1982-2011)
Projected GS signal, A1B scenario
10 simulations (ENSEMBLES)
 DJF and MAM changes can be explained by dominantly GHG driven scenarios
 None of the 10 RCM climate projections capture the observed annual and seasonal
warming in summer (JJA) and autumn (SON).
Precipitation trends in the Baltic Sea Region
(1979-2008)
Observed (CRU3, GPCC6, GPCP)
Projected GS signal (ENSEMBLES)
In winter (DJF) none of the 59
segments derived from 2,000 year
paleo-simulations yield a positive
trend of precipitation as strong as that
observed. There is less than 5%
probability that observed positive
trends in winter be due to natural
(internal + external) variability alone
(with less than 5% risk).
In spring (MAM), summer (JJA) and Annual trends externally forced changes are not detectable. However
observed trends lie within the range of changes described by 10 climate change scenarios, indicating that
also in the scenarios a systematic trend reflecting external forcing is not detectable (< 5% risk).
In autumn (SON) the observed negative trends of precipitation contradicts the upward trends suggested by
10 climate change scenarios, irrespective of the observed dataset used.
Precipitation in the Med Sea Region
(Over land, 1966-2005, CMIP3)
(Barkhordarian et al , Climate Dynamics 2013)
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Mean sea-level pressure in the Med Sea
Region (SLP)
Observed SLP changes
Projected GS signal
DJF
DJF
MAM
MAM
JJA
JJA
SON
SON
Observed SLP 1974-2005
Projected GS signal
Simulated GS signal
DJF
MAM
JJA
SON
Annual
(Barkhordarian A.,2012b)
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Surface solar radiation in the Med Sea Region
(1985-2004)
Observed 1985-2004
Projected 22 models (A1B scenario)
+6.4
W/m2/decade
+5.4
DJF
MAM
JJA
SON
Annual
Decrease of anthropogenic aerosols due to:
more effective clean-air regulations, energy consumption
decline in the Eastern European economy in the late 1980s, closure of dirty factories
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Solar surface radiation in the Baltic Sea
Region, 1984-2005
Observed 1984-2005 (MFG Satellites)
Projected GS signal (ENSEMBLES)
1880-2004 development of sulphur dioxide
emissions in Europe (Unit: Tg SO2). (after Vestreng
et al., 2007 in BACC-2 report, Sec 6.3 by HC
Hansson
 A possible candidate to explain the observed deviations of the trends in summer and
autumn, which are not captured by 10 RCMs, is the effect of changing regional aerosol
loads
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Changes in Large-scale circulation (SON)
in terms of sea level pressure
Projected GS signal
pattern (RCMs)
Observed trend pattern
(1978-2009)
 Observed trend pattern shows areas of decrease in SLP over the Med. Sea and areas
of increase in SLP over the northern Europe. Observed trend pattern of SLP in SON
contradicts regional climate projections.
 The mismatch between projected and observed precipitation in autumn is
already present in the atmospheric circulation.
Conclusions
Precipitation:
An influence of GS signal is detectable in winter and early spring, observed
precipitation changes are several times larger than the projected response to GS
forcing. The most striking inconsistency, however, is the contradiction between
projected drying and the observed increase in precipitation in late summer and
autumn
Obtained results are insensitive to the removal of NAO fingerprint. And are
robust against using a high resolution climate model.
The analysis of large-scale circulation patterns, in terms of mean and extreme
sea-level pressure and Geopotential height at 500 hPa, confirms the
inconsistency detected for precipitation.
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Conclusion
Our analysis indicates that the recent regional climate change in Europe cannot
be explained, in the framework of our present knowledge, without reference to
elevated greenhouse gases. However, in summer and fall, the river „GHGs“ is
insufficient in explaining the recent change.
Possible causes:
a) Suggestion for response to GHG driver by climate model is inaccurate.
b) Other drivers are significant, in particular the non-maintenance of the earlier
atmospheric aerosol-load (Problem; we have no regional quantified guess
patterns)
c) Natural variability is underestimated by historical simulation with climate
model - the change is still within the range of natural variability.
Some science is settled, but lots of science is not settled.
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Michael Schrenk, © von Storch, HZG
Michael Schrenk, © von Storch, HZG
Michael Schrenk, © von Storch, HZG
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